Separation of a subcutaneous cardiac signal from a plurality of composite signals

ABSTRACT

A cardiac monitoring and/or stimulation method and systems provide monitoring, defibrillation and/or pacing therapies, including systems detecting and/or treating cardiac arrhythmia. A system includes a housing coupled to a plurality of electrodes configured for subcutaneous non-intrathoracic sensing. A signal processor receives a plurality of composite signals associated with a plurality of sources, separates a signal from the plurality of composite signals using blind source separation, and identifies a cardiac signal. The signal processor may iteratively separate signals from the plurality of composite signals until the cardiac signal is identified. A method of signal separation includes detecting a plurality of composite signals at a plurality of locations, separating a signal using blind source separation, and identifying a cardiac signal. The separation may include a principal component analysis and/or an independent component analysis. The composite signals may be filtered before separation using band-pass filtering, adaptive, or other filters.

RELATED APPLICATIONS

This application claims the benefit of Provisional Patent ApplicationSer. No. 60/462,272, filed on Apr. 11, 2003, to which priority isclaimed pursuant to 35 U.S.C. §119(e) and which is hereby incorporatedherein by reference.

FIELD OF THE INVENTION

The present invention relates generally to implantable medical devicesand, more particularly, to subcutaneous cardiac sensing and/orstimulation devices employing cardiac signal separation.

BACKGROUND OF THE INVENTION

The healthy heart produces regular, synchronized contractions. Rhythmiccontractions of the heart are normally controlled by the sinoatrial (SA)node, which is a group of specialized cells located in the upper rightatrium. The SA node is the normal pacemaker of the heart, typicallyinitiating 60–100 heartbeats per minute. When the SA node is pacing theheart normally, the heart is said to be in normal sinus rhythm.

If the heart's electrical activity becomes uncoordinated or irregular,the heart is denoted to be arrhythmic. Cardiac arrhythmia impairscardiac efficiency and can be a potential life-threatening event.Cardiac arrhythmias have a number of etiological sources, includingtissue damage due to myocardial infarction, infection, or degradation ofthe heart's ability to generate or synchronize the electrical impulsesthat coordinate contractions.

Bradycardia occurs when the heart rhythm is too slow. This condition maybe caused, for example, by impaired function of the SA node, denotedsick sinus syndrome, or by delayed propagation or blockage of theelectrical impulse between the atria and ventricles. Bradycardiaproduces a heart rate that is too slow to maintain adequate circulation.

When the heart rate is too rapid, the condition is denoted tachycardia.Tachycardia may have its origin in either the atria or the ventricles.Tachycardias occurring in the atria of the heart, for example, includeatrial fibrillation and atrial flutter. Both conditions arecharacterized by rapid contractions of the atria. Besides beinghemodynamically inefficient, the rapid contractions of the atria canalso adversely affect the ventricular rate.

Ventricular tachycardia occurs, for example, when electrical activityarises in the ventricular myocardium at a rate more rapid than thenormal sinus rhythm. Ventricular tachycardia can quickly degenerate intoventricular fibrillation. Ventricular fibrillation is a conditiondenoted by extremely rapid, uncoordinated electrical activity within theventricular tissue. The rapid and erratic excitation of the ventriculartissue prevents synchronized contractions and impairs the heart'sability to effectively pump blood to the body, which is a fatalcondition unless the heart is returned to sinus rhythm within a fewminutes.

Implantable cardiac rhythm management systems have been used as aneffective treatment for patients with serious arrhythmias. These systemstypically include one or more leads and circuitry to sense signals fromone or more interior and/or exterior surfaces of the heart. Such systemsalso include circuitry for generating electrical pulses that are appliedto cardiac tissue at one or more interior and/or exterior surfaces ofthe heart. For example, leads extending into the patient's heart areconnected to electrodes that contact the myocardium for sensing theheart's electrical signals and for delivering pulses to the heart inaccordance with various therapies for treating arrhythmias.

Typical implantable cardioverter/defibrillators (ICDs) include one ormore endocardial leads to which at least one defibrillation electrode isconnected. Such ICDs are capable of delivering high-energy shocks to theheart, interrupting the ventricular tachyarrhythmia or ventricularfibrillation, and allowing the heart to resume normal sinus rhythm. ICDsmay also include pacing functionality.

Although ICDs are very effective at preventing Sudden Cardiac Death(SCD), most people at risk of SCD are not provided with implantabledefibrillators. Primary reasons for this unfortunate reality include thelimited number of physicians qualified to perform transvenouslead/electrode implantation, a limited number of surgical facilitiesadequately equipped to accommodate such cardiac procedures, and alimited number of the at-risk patient population that may safely undergothe required endocardial or epicardial lead/electrode implant procedure.Subcutaneous ICDs are being developed to address these issues.

There is a need for improved electrode configurations specific to theneeds of subcutaneous electrode placement and to address the noiseassociated with subcutaneous electrode placement. There is a furtherneed for a method of improving the signal to noise ratio of the cardiacsignal in subcutaneous ICDs. The present invention fulfills these andother needs, and addresses deficiencies in known systems and techniques.

SUMMARY OF THE INVENTION

The present invention is directed to cardiac monitoring and/orstimulation methods and systems that, in general, provide transthoracicmonitoring, defibrillation therapies, pacing therapies, or a combinationof these capabilities. Embodiments of the present invention includethose directed to subcutaneous cardiac monitoring and/or stimulationmethods and systems that detect and/or treat cardiac activity orarrhythmias.

According to one embodiment of the invention, a medical system includesa housing having a medical device disposed within the housing. Thehousing is coupled to a plurality of electrodes configured forsubcutaneous non-intrathoracic sensing. A signal processor is coupled tothe plurality of electrodes and configured to receive a plurality ofcomposite signals associated with a plurality of sources sensed by atleast some of the electrodes. The signal processor is further configuredto separate a signal from the plurality of composite signals andidentify the separated signal as a cardiac signal.

In another embodiment of the present invention, the signal processoriteratively separates signals from the plurality of composite signalsuntil the cardiac signal is identified. The processor may include afilter configured to filter the plurality of composite signals prior toseparating the signal.

In another aspect of the present invention, a method of signalseparation includes detecting a plurality of composite signals at aplurality of subcutaneous non-intrathoracic locations, the plurality ofcomposite signals associated with a plurality of sources. A signal isseparated, using blind source separation, from the plurality ofcomposite signals, and identified as a cardiac signal. The method mayfurther include a principal component analysis and/or an independentcomponent analysis to perform the blind source separation. The compositesignals may be filtered before separation using band-pass filtering,adaptive, or other filters.

In another embodiment of the present invention, an estimate of thespatial covariance matrix for a composite signal matrix is formed fromthe plurality of composite signals. Independent component analysis andprincipal component analysis may be performed using the estimate of thespatial covariance matrix, producing a set of eigenvalues and associatedeigenvectors. An eigenvector associated with a largest magnitudeeigenvalue may be used to separate the cardiac signal from the pluralityof composite signals by multiplying the composite signal matrix by theeigenvector.

The signal may be separated iteratively from the plurality of compositesignals using an eigenvector associated with a next-largest magnitudeeigenvalue for each iteration, until the cardiac signal is identified.The cardiac signal may be identified using a local peak density (LPD) ofthe separated signal, wherein the LPD is within a predetermined range.The cardiac signal may also be identified using beat detection on theseparated signal, wherein a beat rate is within a predetermined range,or by using a local rate of occurrence of significant points in theseparated signal, wherein the local rate of occurrence is within apredetermined range. The cardiac signal may also be identified using amorphology of the separated signal, wherein the morphology satisfies aphysiological characteristic.

The above summary of the present invention is not intended to describeeach embodiment or every implementation of the present invention.Advantages and attainments, together with a more complete understandingof the invention, will become apparent and appreciated by referring tothe following detailed description and claims taken in conjunction withthe accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIGS. 1A and 1B are views of a transthoracic cardiac sensing and/orstimulation device as implanted in a patient in accordance with anembodiment of the present invention;

FIG. 1C is a block diagram illustrating various components of atransthoracic cardiac sensing and/or stimulation device in accordancewith an embodiment of the present invention;

FIG. 1D is a block diagram illustrating various processing and detectioncomponents of a transthoracic cardiac sensing and/or stimulation devicein accordance with an embodiment of the present invention;

FIG. 2 is a diagram illustrating components of a transthoracic cardiacsensing and/or stimulation device including an electrode array inaccordance with an embodiment of the present invention;

FIG. 3 is a block diagram illustrating uses of signal separation inaccordance with the present invention;

FIG. 4 is a block diagram of a cardiac sensing methodology incorporatingsignal separation in accordance with the present invention;

FIG. 5 is a block diagram of a signal separation process in accordancewith the present invention;

FIG. 6 is an expanded block diagram of the process illustrated in FIG.5, illustrating an iterative independent component analysis inaccordance with the present invention; and

FIG. 7 is a graph illustrating the results of a signal separationprocess in accordance with the present invention.

While the invention is amenable to various modifications and alternativeforms, specifics thereof have been shown by way of example in thedrawings and will be described in detail below. It is to be understood,however, that the intention is not to limit the invention to theparticular embodiments described. On the contrary, the invention isintended to cover all modifications, equivalents, and alternativesfalling within the scope of the invention as defined by the appendedclaims.

DETAILED DESCRIPTION OF VARIOUS EMBODIMENTS

In the following description of the illustrated embodiments, referencesare made to the accompanying drawings, which form a part hereof, and inwhich is shown by way of illustration, various embodiments in which theinvention may be practiced. It is to be understood that otherembodiments may be utilized, and structural and functional changes maybe made without departing from the scope of the present invention.

An implanted device according to the present invention may include oneor more of the features, structures, methods, or combinations thereofdescribed hereinbelow. For example, a cardiac monitor or a cardiacstimulator may be implemented to include one or more of the advantageousfeatures and/or processes described below. It is intended that such amonitor, stimulator, or other implanted or partially implanted deviceneed not include all of the features described herein, but may beimplemented to include selected features that provide for uniquestructures and/or functionality. Such a device may be implemented toprovide a variety of therapeutic or diagnostic functions.

In general terms, an implantable noise canceling lead system may be usedwith a subcutaneous cardiac monitoring and/or stimulation device. Onesuch device is an implantable transthoracic cardiac sensing and/orstimulation (ITCS) device that may be implanted under the skin in thechest region of a patient. The ITCS device may, for example, beimplanted subcutaneously such that all or selected elements of thedevice are positioned on the patient's front, back, side, or other bodylocations suitable for sensing cardiac activity and delivering cardiacstimulation therapy. It is understood that elements of the ITCS devicemay be located at several different body locations, such as in thechest, abdominal, or subclavian region with electrode elementsrespectively positioned at different regions near, around, in, or on theheart.

The primary housing (e.g., the active or non-active can) of the ITCSdevice, for example, may be configured for positioning outside of therib cage at an intercostal or subcostal location, within the abdomen, orin the upper chest region (e.g., subclavian location, such as above thethird rib). In one implementation, one or more electrodes may be locatedon the primary housing and/or at other locations about, but not indirect contact with the heart, great vessel or coronary vasculature.

In another implementation, one or more noise canceling leadsincorporating electrodes may be located in direct contact with theheart, great vessel or coronary vasculature, such as via one or moreleads implanted by use of conventional transvenous delivery approaches.In a further implementation, for example, one or more subcutaneous noisecanceling electrode subsystems or electrode arrays may be used to sensecardiac activity and deliver cardiac stimulation energy in an ITCSdevice configuration employing an active can or a configurationemploying a non-active can. Electrodes may be situated at anteriorand/or posterior locations relative to the heart. Examples of noisecanceling subcutaneous electrodes and electrode arrays are described incommonly owned US Publication No. 2004/0230243, which is herebyincorporated herein by reference.

Certain configurations illustrated herein are generally described ascapable of implementing various functions traditionally performed by animplantable cardioverter/defibrillator (ICD), and may operate innumerous cardioversion/defibrillation modes as are known in the art.Exemplary ICD circuitry, structures and functionality, aspects of whichmay be incorporated in an ITCS device of a type that may benefit fromnoise canceling electrode configurations, are disclosed in commonlyowned U.S. Pat. Nos. 5,133,353; 5,179,945; 5,314,459; 5,318,597;5,620,466; and 5,662,688, which are hereby incorporated herein byreference in their respective entireties.

In particular configurations, systems and methods may perform functionstraditionally performed by pacemakers, such as providing various pacingtherapies as are known in the art, in addition tocardioversion/defibrillation therapies. Exemplary pacemaker circuitry,structures and functionality, aspects of which may be incorporated in anITCS device of a type that may benefit from signal separation, aredisclosed in commonly owned U.S. Pat. Nos. 4,562,841; 5,284,136;5,376,106; 5,036,849; 5,540,727; 5,836,987; 6,044,298; and 6,055,454,which are hereby incorporated herein by reference in their respectiveentireties. It is understood that ITCS device configurations may providefor non-physiologic pacing support in addition to, or to the exclusionof, bradycardia and/or anti-tachycardia pacing therapies.

An ITCS device in accordance with the present invention may implementdiagnostic and/or monitoring functions as well as provide cardiacstimulation therapy. Exemplary cardiac monitoring circuitry, structuresand functionality, aspects of which may be incorporated in an ITCSdevice of a type that may benefit from noise canceling electrodeconfigurations, are disclosed in commonly owned U.S. Pat. Nos.5,313,953; 5,388,578; and 5,411,031, which are hereby incorporatedherein by reference in their respective entireties.

An ITCS device may be used to implement various diagnostic functions,which may involve performing rate-based, pattern and rate-based, and/ormorphological tachyarrhythmia discrimination analyses. Subcutaneous,cutaneous, and/or external sensors may be employed to acquirephysiologic and non-physiologic information for purposes of enhancingtachyarrhythmia detection and termination. It is understood thatconfigurations, features, and combination of features described in theinstant disclosure may be implemented in a wide range of implantablemedical devices, and that such embodiments and features are not limitedto the particular devices described herein.

Referring now to FIGS. 1A and 1B of the drawings, there is shown aconfiguration of a transthoracic cardiac sensing and/or stimulation(ITCS) device having components implanted in the chest region of apatient at different locations. In the particular configuration shown inFIGS. 1A and 1B, the ITCS device includes a housing 102 within whichvarious cardiac sensing, detection, processing, and energy deliverycircuitry may be housed. It is understood that the components andfunctionality depicted in the figures and described herein may beimplemented in hardware, software, or a combination of hardware andsoftware. It is further understood that the components and functionalitydepicted as separate or discrete blocks/elements in the figures may beimplemented in combination with other components and functionality, andthat the depiction of such components and functionality in individual orintegral form is for purposes of clarity of explanation, and not oflimitation.

Communications circuitry is disposed within the housing 102 forfacilitating communication between the ITCS device and an externalcommunication device, such as a portable or bed-side communicationstation, patient-carried/worn communication station, or externalprogrammer, for example. The communications circuitry may alsofacilitate unidirectional or bidirectional communication with one ormore external, cutaneous, or subcutaneous physiologic or non-physiologicsensors. The housing 102 is typically configured to include one or moreelectrodes (e.g., can electrode and/or indifferent electrode). Althoughthe housing 102 is typically configured as an active can, it isappreciated that a non-active can configuration may be implemented, inwhich case at least two electrodes spaced apart from the housing 102 areemployed.

In the configuration shown in FIGS. 1A and 1B, a subcutaneous electrode104 may be positioned under the skin in the chest region and situateddistal from the housing 102. The subcutaneous and, if applicable,housing electrode(s) may be positioned about the heart at variouslocations and orientations, such as at various anterior and/or posteriorlocations relative to the heart. The subcutaneous electrode 104 iscoupled to circuitry within the housing 102 via a lead assembly 106. Oneor more conductors (e.g., coils or cables) are provided within the leadassembly 106 and electrically couple the subcutaneous electrode 104 withcircuitry in the housing 102. One or more sense, sense/pace ordefibrillation electrodes may be situated on the elongated structure ofthe electrode support, the housing 102, and/or the distal electrodeassembly (shown as subcutaneous electrode 104 in the configuration shownin FIGS. 1A and 1B).

In one configuration, the lead assembly 106 is generally flexible andhas a construction similar to conventional implantable, medicalelectrical leads (e.g., defibrillation leads or combineddefibrillation/pacing leads). In another configuration, the leadassembly 106 is constructed to be somewhat flexible, yet has an elastic,spring, or mechanical memory that retains a desired configuration afterbeing shaped or manipulated by a clinician. For example, the leadassembly 106 may incorporate a gooseneck or braid system that may bedistorted under manual force to take on a desired shape. In this manner,the lead assembly 106 may be shape-fit to accommodate the uniqueanatomical configuration of a given patient, and generally retains acustomized shape after implantation. Shaping of the lead assembly 106according to this configuration may occur prior to, and during, ITCSdevice implantation.

In accordance with a further configuration, the lead assembly 106includes a rigid electrode support assembly, such as a rigid elongatedstructure that positionally stabilizes the subcutaneous electrode 104with respect to the housing 102. In this configuration, the rigidity ofthe elongated structure maintains a desired spacing between thesubcutaneous electrode 104 and the housing 102, and a desiredorientation of the subcutaneous electrodel 104/housing 102 relative tothe patient's heart. The elongated structure may be formed from astructural plastic, composite, or metallic material, and comprises, oris covered by, a biocompatible material. Appropriate electricalisolation between the housing 102 and subcutaneous electrode 104 isprovided in cases where the elongated structure is formed from anelectrically conductive material, such as metal.

In one configuration, the rigid electrode support assembly and thehousing 102 define a unitary structure (e.g., a single housing/unit).The electronic components and electrode conductors/connectors aredisposed within or on the unitary ITCS device housing/electrode supportassembly. At least two electrodes are supported on the unitary structurenear opposing ends of the housing/electrode support assembly. Theunitary structure may have an arcuate or angled shape, for example.

According to another configuration, the rigid electrode support assemblydefines a physically separable unit relative to the housing 102. Therigid electrode support assembly includes mechanical and electricalcouplings that facilitate mating engagement with correspondingmechanical and electrical couplings of the housing 102. For example, aheader block arrangement may be configured to include both electricaland mechanical couplings that provide for mechanical and electricalconnections between the rigid electrode support assembly and housing102. The header block arrangement may be provided on the housing 102 orthe rigid electrode support assembly. Alternatively, amechanical/electrical coupler may be used to establish mechanical andelectrical connections between the rigid electrode support assembly andhousing 102. In such a configuration, a variety of different electrodesupport assemblies of varying shapes, sizes, and electrodeconfigurations may be made available for physically and electricallyconnecting to a standard ITCS device housing 102.

It is noted that the electrodes and the lead assembly 106 may beconfigured to assume a variety of shapes. For example, the lead assembly106 may have a wedge, chevron, flattened oval, or a ribbon shape, andthe subcutaneous electrode 104 may comprise a number of spacedelectrodes, such as an array or band of electrodes. Moreover, two ormore subcutaneous electrodes 104 may be mounted to multiple electrodesupport assemblies 106 to achieve a desired spaced relationship amongstsubcutaneous electrodes 104.

An ITCS device may incorporate circuitry, structures and functionalityof the subcutaneous implantable medical devices disclosed in commonlyowned U.S. Pat. Nos. 5,203,348; 5,230,337; 5,360,442; 5,366,496;5,397,342; 5,391,200; 5,545,202; 5,603,732; and 5,916,243, which arehereby incorporated herein by reference in their respective entireties.

FIG. 1C is a block diagram depicting various components of an ITCSdevice in accordance with one configuration. According to thisconfiguration, the ITCS device incorporates a processor-based controlsystem 205 which includes a micro-processor 206 coupled to appropriatememory (volatile and non-volatile) 209, it being understood that anylogic-based control architecture may be used. The control system 205 iscoupled to circuitry and components to sense, detect, and analyzeelectrical signals produced by the heart and deliver electricalstimulation energy to the heart under predetermined conditions to treatcardiac arrhythmias. In certain configurations, the control system 205and associated components also provide pacing therapy to the heart. Theelectrical energy delivered by the ITCS device may be in the form of lowenergy pacing pulses or high-energy pulses for cardioversion ordefibrillation.

Cardiac signals are sensed using the subcutaneous electrode(s) 214 andthe can or indifferent electrode 207 provided on the ITCS devicehousing. Cardiac signals may also be sensed using only the subcutaneouselectrodes 214, such as in a non-active can configuration. As such,unipolar, bipolar, or combined unipolar/bipolar electrode configurationsas well as multi-element noise canceling electrodes and combinations ofnoise canceling and standard electrodes may be employed. The sensedcardiac signals are received by sensing circuitry 204, which includessense amplification circuitry and may also include filtering circuitryand an analog-to-digital (A/D) converter. The sensed cardiac signalsprocessed by the sensing circuitry 204 may be received by noisereduction circuitry 203, which may further reduce noise before signalsare sent to the detection circuitry 202.

Noise reduction circuitry 203 may also be incorporated after sensingcircuitry 204 in cases where high power or computationally intensivenoise reduction algorithms are required. The noise reduction circuitry203, by way of amplifiers used to perform operations with the electrodesignals, may also perform the function of the sensing circuitry 204.Combining the functions of sensing circuitry 204 and noise reductioncircuitry 203 may be useful to minimize the necessary componentry andlower the power requirements of the system.

In the illustrative configuration shown in FIG. 1C, the detectioncircuitry 202 is coupled to, or otherwise incorporates, noise reductioncircuitry 203. The noise reduction circuitry 203 operates to improve theSNR of sensed cardiac signals by removing noise content of the sensedcardiac signals introduced from various sources. Typical types oftransthoracic cardiac signal noise includes electrical noise and noiseproduced from skeletal muscles, for example. A number of methodologiesfor improving the SNR of sensed cardiac signals in the presence ofskeletal muscular induced noise, including signal separation techniquesincorporating combinations of electrodes and noise cancelingmulti-element electrodes, are described hereinbelow.

Detection circuitry 202 typically includes a signal processor thatcoordinates analysis of the sensed cardiac signals and/or other sensorinputs to detect cardiac arrhythmias, such as, in particular,tachyarrhythmia. Rate based and/or morphological discriminationalgorithms may be implemented by the signal processor of the detectioncircuitry 202 to detect and verify the presence and severity of anarrhythmic episode. Exemplary arrhythmia detection and discriminationcircuitry, structures, and techniques, aspects of which may beimplemented by an ITCS device of a type that may benefit from noisecanceling electrode configurations, are disclosed in commonly owned U.S.Pat. Nos. 5,301,677 and 6,438,410, which are hereby incorporated hereinby reference in their respective entireties. Arrhythmia detectionmethodologies particularly well suited for implementation insubcutaneous cardiac monitoring and/or stimulation systems are describedhereinbelow.

The detection circuitry 202 communicates cardiac signal information tothe control system 205. Memory circuitry 209 of the control system 205contains parameters for operating in various sensing, defibrillation,and, if applicable, pacing modes, and stores data indicative of cardiacsignals received by the detection circuitry 202. The memory circuitry209 may also be configured to store historical ECG and therapy data,which may be used for various purposes and transmitted to an externalreceiving device as needed or desired.

In certain configurations, the ITCS device may include diagnosticscircuitry 210. The diagnostics circuitry 210 typically receives inputsignals from the detection circuitry 202 and the sensing circuitry 204.The diagnostics circuitry 210 provides diagnostics data to the controlsystem 205, it being understood that the control system 205 mayincorporate all or part of the diagnostics circuitry 210 or itsfunctionality. The control system 205 may store and use informationprovided by the diagnostics circuitry 210 for a variety of diagnosticspurposes. This diagnostic information may be stored, for example,subsequent to a triggering event or at predetermined intervals, and mayinclude system diagnostics, such as power source status, therapydelivery history, and/or patient diagnostics. The diagnostic informationmay take the form of electrical signals or other sensor data acquiredimmediately prior to therapy delivery.

According to a configuration that provides cardioversion anddefibrillation therapies, the control system 205 processes cardiacsignal data received from the detection circuitry 202 and initiatesappropriate tachyarrhythmia therapies to terminate cardiac arrhythmicepisodes and return the heart to normal sinus rhythm. The control system205 is coupled to shock therapy circuitry 216. The shock therapycircuitry 216 is coupled to the subcutaneous electrode(s) 214 and thecan or indifferent electrode 207 of the ITCS device housing. Uponcommand, the shock therapy circuitry 216 delivers cardioversion anddefibrillation stimulation energy to the heart in accordance with aselected cardioversion or defibrillation therapy. In a lesssophisticated configuration, the shock therapy circuitry 216 iscontrolled to deliver defibrillation therapies, in contrast to aconfiguration that provides for delivery of both cardioversion anddefibrillation therapies. Exemplary ICD high energy delivery circuitry,structures and functionality, aspects of which may be incorporated in anITCS device of a type that may benefit from aspects of the presentinvention are disclosed in commonly owned U.S. Pat. Nos. 5,372,606;5,411,525; 5,468,254; and 5,634,938, which are hereby incorporatedherein by reference in their respective entireties.

In accordance with another configuration, an ITCS device may incorporatea cardiac pacing capability in addition to cardioversion and/ordefibrillation capabilities. As is shown in dotted lines in FIG. 1C, theITCS device may include pacing therapy circuitry 230, which is coupledto the control system 205 and the subcutaneous and can/indifferentelectrodes 214, 207. Upon command, the pacing therapy circuitry deliverspacing pulses to the heart in accordance with a selected pacing therapy.Control signals, developed in accordance with a pacing regimen bypacemaker circuitry within the control system 205, are initiated andtransmitted to the pacing therapy circuitry 230 where pacing pulses aregenerated. A pacing regimen may be modified by the control system 205.

A number of cardiac pacing therapies may be useful in a transthoraciccardiac monitoring and/or stimulation device. Such cardiac pacingtherapies may be delivered via the pacing therapy circuitry 230 as shownin FIG. 1C. Alternatively, cardiac pacing therapies may be delivered viathe shock therapy circuitry 216, which effectively obviates the need forseparate pacemaker circuitry.

The ITCS device shown in FIG. 1C may be configured to receive signalsfrom one or more physiologic and/or non-physiologic sensors. Dependingon the type of sensor employed, signals generated by the sensors may becommunicated to transducer circuitry coupled directly to the detectioncircuitry 202 or indirectly via the sensing circuitry 204. It is notedthat certain sensors may transmit sense data to the control system 205without processing by the detection circuitry 202.

Communications circuitry 218 is coupled to the microprocessor 206 of thecontrol system 205. The communications circuitry 218 allows the ITCSdevice to communicate with one or more receiving devices or systemssituated external to the ITCS device. By way of example, the ITCS devicemay communicate with a patient-worn, portable or bedside communicationsystem via the communications circuitry 218. In one configuration, oneor more physiologic or non-physiologic sensors (subcutaneous, cutaneous,or external of patient) may be equipped with a short-range wirelesscommunication interface, such as an interface conforming to a knowncommunications standard, such as Bluetooth or IEEE 802 standards. Dataacquired by such sensors may be communicated to the ITCS device via thecommunications circuitry 218. It is noted that physiologic ornon-physiologic sensors equipped with wireless transmitters ortransceivers may communicate with a receiving system external of thepatient.

The communications circuitry 218 may allow the ITCS device tocommunicate with an external programmer. In one configuration, thecommunications circuitry 218 and the programmer unit (not shown) use awire loop antenna and a radio frequency telemetric link, as is known inthe art, to receive and transmit signals and data between the programmerunit and communications circuitry 218. In this manner, programmingcommands and data are transferred between the ITCS device and theprogrammer unit during and after implant. Using a programmer, aphysician is able to set or modify various parameters used by the ITCSdevice. For example, a physician may set or modify parameters affectingsensing, detection, pacing, and defibrillation functions of the ITCSdevice, including pacing and cardioversion/defibrillation therapy modes.

Typically, the ITCS device is encased and hermetically sealed in ahousing suitable for implanting in a human body as is known in the art.Power to the ITCS device is supplied by an electrochemical power source220 housed within the ITCS device. In one configuration, the powersource 220 includes a rechargeable battery. According to thisconfiguration, charging circuitry is coupled to the power source 220 tofacilitate repeated non-invasive charging of the power source 220. Thecommunications circuitry 218, or separate receiver circuitry, isconfigured to receive RF energy transmitted by an external RF energytransmitter. The ITCS device may, in addition to a rechargeable powersource, include a non-rechargeable battery. It is understood that arechargeable power source need not be used, in which case a long-lifenon-rechargeable battery is employed.

FIG. 1D illustrates a configuration of detection circuitry 302 of anITCS device, which includes one or both of rate detection circuitry 310and morphological analysis circuitry 312. Detection and verification ofarrhythmias may be accomplished using rate-based discriminationalgorithms as known in the art implemented by the rate detectioncircuitry 310. Arrhythmic episodes may also be detected and verified bymorphology-based analysis of sensed cardiac signals as is known in theart. Tiered or parallel arrhythmia discrimination algorithms may also beimplemented using both rate-based and morphologic-based approaches.Further, a rate and pattern-based arrhythmia detection anddiscrimination approach may be employed to detect and/or verifyarrhythmic episodes, such as the approach disclosed in U.S. Pat. Nos.6,487,443; 6,259,947; 6,141,581; 5,855,593; and 5,545,186, which arehereby incorporated herein by reference in their respective entireties.

The detection circuitry 302, which is coupled to a microprocessor 306,may be configured to incorporate, or communicate with, specializedcircuitry for processing sensed cardiac signals in manners particularlyuseful in a transthoracic cardiac sensing and/or stimulation device. Asis shown by way of example in FIG. 1D, the detection circuitry 302 mayreceive information from multiple physiologic and non-physiologicsensors. As illustrated, transthoracic acoustics may be monitored usingan appropriate acoustic sensor. Heart sounds, for example, may bedetected and processed by cardiac acoustic processing circuitry 318 fora variety of purposes. The acoustics data is transmitted to thedetection circuitry 302, via a hardwire or wireless link, and used toenhance cardiac signal detection. For example, acoustics may be used todiscriminate normal cardiac sinus rhythm with electrical noise frompotentially lethal arrhythmias, such as ventricular tachycardia orventricular fibrillation.

The detection circuitry 302 may also receive information from one ormore sensors that monitor skeletal muscle activity. In addition tocardiac activity signals, transthoracic electrodes readily detectskeletal muscle signals. Such skeletal muscle signals may be used todetermine the activity level of the patient. In the context of cardiacsignal detection, such skeletal muscle signals are considered artifactsof the cardiac activity signal, which may be viewed as noise. Processingcircuitry 316 receives signals from one or more skeletal muscle sensors,and transmits processed skeletal muscle signal data to the detectioncircuitry 302. This data may be used to discriminate normal cardiacsinus rhythm with skeletal muscle noise from cardiac arrhythmias.

As was previously discussed, the detection circuitry 302 is coupled to,or otherwise incorporates, noise-processing circuitry 314. The noiseprocessing circuitry 314 processes sensed cardiac signals to improve theSNR of sensed cardiac signals by reducing noise content of the sensedcardiac signals.

The components, functionality, and structural configurations depicted inFIGS. 1A–1D are intended to provide an understanding of various featuresand combination of features that may be incorporated in an ITCS device.It is understood that a wide variety of ITCS and other implantablecardiac monitoring and/or stimulation device configurations arecontemplated, ranging from relatively sophisticated to relatively simpledesigns. As such, particular ITCS or cardiac monitoring and/orstimulation device configurations may include particular features asdescribed herein, while other such device configurations may excludeparticular features described herein.

In accordance with embodiments of the invention, an ITCS device may beimplemented to include a subcutaneous electrode system that provides forone or both of cardiac sensing and arrhythmia therapy delivery.According to one approach, an ITCS device may be implemented as achronically implantable system that performs monitoring, diagnosticand/or therapeutic functions. The ITCS device may automatically detectand treat cardiac arrhythmias. In one configuration, the ITCS deviceincludes a pulse generator and one or more electrodes that are implantedsubcutaneously in the chest region of the body, such as in the anteriorthoracic region of the body. The ITCS device may be used to provideatrial and ventricular therapy for bradycardia and tachycardiaarrhythmias. Tachyarrhythmia therapy may include cardioversion,defibrillation and anti-tachycardia pacing (ATP), for example, to treatatrial or ventricular tachycardia or fibrillation. Bradycardia therapymay include temporary post-shock pacing for bradycardia or asystole.Methods and systems for implementing post-shock pacing for bradycardiaor asystole are described in commonly owned US Publication No.2004/0172066, which is incorporated herein by reference in its entirety.

In one configuration, an ITCS device according to one approach mayutilize conventional pulse generator and subcutaneous electrode implanttechniques. The pulse generator device and electrodes may be chronicallyimplanted subcutaneously. Such an ITCS may be used to automaticallydetect and treat arrhythmias similarly to conventional implantablesystems. In another configuration, the ITCS device may comprise aunitary structure (e.g., a single housing/unit). The electroniccomponents and electrode conductors/connectors are disposed within or onthe unitary ITCS device housing/electrode support assembly.

The ITCS device contains the electronics and may be similar to aconventional implantable defibrillator. High voltage shock therapy maybe delivered between two or more electrodes, one of which may be thepulse generator housing (e.g., can), placed subcutaneously in thethoracic region of the body.

Additionally or alternatively, the ITCS device may also provide lowerenergy electrical stimulation for bradycardia therapy. The ITCS devicemay provide brady pacing similarly to a conventional pacemaker. The ITCSdevice may provide temporary post-shock pacing for bradycardia orasystole. Sensing and/or pacing may be accomplished using sense/paceelectrodes positioned on an electrode subsystem also incorporating shockelectrodes, or by separate electrodes implanted subcutaneously.

The ITCS device may detect a variety of physiological signals that maybe used in connection with various diagnostic, therapeutic or monitoringimplementations. For example, the ITCS device may include sensors orcircuitry for detecting respiratory system signals, cardiac systemsignals, and signals related to patient activity. In one embodiment, theITCS device senses intrathoracic impedance, from which variousrespiratory parameters may be derived, including, for example,respiratory tidal volume and minute ventilation. Sensors and associatedcircuitry may be incorporated in connection with an ITCS device fordetecting one or more body movement or body position related signals.For example, accelerometers and GPS devices may be employed to detectpatient activity, patient location, body orientation, or torso position.

The ITCS device may be used within the structure of an advanced patientmanagement (APM) system. Advanced patient management systems may allowphysicians to remotely and automatically monitor cardiac and respiratoryfunctions, as well as other patient conditions. In one example,implantable cardiac rhythm management systems, such as cardiacpacemakers, defibrillators, and resynchronization devices, may beequipped with various telecommunications and information technologiesthat enable real-time data collection, diagnosis, and treatment of thepatient. Various embodiments described herein may be used in connectionwith advanced patient management. Methods, structures, and/or techniquesdescribed herein, which may be adapted to provide for remotepatient/device monitoring, diagnosis, therapy, or other APM relatedmethodologies, can incorporate features of one or more of the followingreferences: U.S. Pat. Nos. 6,221,011; 6,270,457; 6,277,072; 6,280,380;6,312,378; 6,336,903; 6,358,203; 6,368,284; 6,398,728; and 6,440,066,which are hereby incorporated herein by reference.

An ITCS device according to one approach provides an easy to implanttherapeutic, diagnostic or monitoring system. The ITCS system may beimplanted without the need for intravenous or intrathoracic access,providing a simpler, less invasive implant procedure and minimizing leadand surgical complications. In addition, this system would haveadvantages for use in patients for whom transvenous lead systems causecomplications. Such complications include, but are not limited to,surgical complications, infection, insufficient vessel patency,complications associated with the presence of artificial valves, andlimitations in pediatric patients due to patient growth, among others.An ITCS system according to this approach is distinct from conventionalapproaches in that it is preferably configured to include a combinationof two or more electrode subsystems that are implanted subcutaneously inthe anterior thorax.

In one configuration, as is illustrated in FIG. 2, electrode subsystemsof an ITCS system are arranged about a patient's heart 510. The ITCSsystem includes a first electrode subsystem, comprising a can electrode502, and a second electrode subsystem 504 that includes at least twoelectrodes or at least one multi-element electrode. The second electrodesubsystem 504 may comprise a number of electrodes used for sensingand/or electrical stimulation.

In various configurations, the second electrode subsystem 504 maycomprise a combination of electrodes. The combination of electrodes ofthe second electrode subsystem 504 may include coil electrodes, tipelectrodes, ring electrodes, multi-element coils, spiral coils, spiralcoils mounted on non-conductive backing, screen patch electrodes, andother electrode configurations as will be described below. A suitablenon-conductive backing material is silicone rubber, for example.

The can electrode 502 is positioned on the housing 501 that encloses theITCS device electronics. In one embodiment, the can electrode 502comprises the entirety of the external surface of the housing 501. Inother embodiments, various portions of the housing 501 may beelectrically isolated from the can electrode 502 or from tissue. Forexample, the active area of the can electrode 502 may comprise all or aportion of either the anterior or posterior surface of the housing 501to direct current flow in a manner advantageous for cardiac sensingand/or stimulation.

In accordance with one embodiment, the housing 501 may resemble that ofa conventional implantable ICD, and is approximately 20–100 cc involume, with a thickness of 0.4 to 2 cm and with a surface area on eachface of approximately 30 to 100 cm². As previously discussed, portionsof the housing may be electrically isolated from tissue to optimallydirect current flow. For example, portions of the housing 501 may becovered with a non-conductive, or otherwise electrically resistive,material to direct current flow. Suitable non-conductive materialcoatings include those formed from silicone rubber, polyurethane, orparylene, for example.

In addition, or alternatively, all or portions of the housing 501 may betreated to change the electrical conductivity characteristics thereoffor purposes of optimally directing current flow. Various knowntechniques may be employed to modify the surface conductivitycharacteristics of the housing 501, such as by increasing or decreasingsurface conductivity, to optimize current flow. Such techniques mayinclude those that mechanically or chemically alter the surface of thehousing 501 to achieve desired electrical conductivity characteristics.

As was discussed above, cardiac signals collected from subcutaneouslyimplanted electrodes may be corrupted by noise. In addition, certainnoise sources have frequency characteristics similar to those of thecardiac signal. Such noise may lead to over sensing and spurious shocks.Due to the possibility of relatively high amplitude of the noise signaland overlapping frequency content, filtering alone does not lead tocomplete suppression of the noise. In addition, filter performance isnot generally sufficiently robust against the entire class of noisesencountered. Further, known adaptive filtering approaches require areference signal that is often unknown for situations when a patientexperiences VF or high amplitude noise.

An ITCS device according to the present invention may be implemented toinclude a noise rejection/reduction capability to improve noiserejection of cardiac signals sensed by subcutaneous electrodes. Thisnoise rejection/reduction approach advantageously reduces the risk offalse positives for detection algorithms by improving the signal tonoise ratio of the cardiac signal.

In accordance with one approach of the present invention, an ITCS devicemay be implemented to separate cardiac signals from noise in a robustmanner using a blind source separation (BSS) technique. It is understoodthat all or certain aspects of the BSS technique described below may beimplemented in a device or system (implantable or non-implantable) otherthan an ITCS device, and that the description of BSS techniquesimplemented in an ITCS device is provided for purposes of illustration,and not of limitation. For example, algorithms that implement a BSStechnique as described below may be implemented for use by an implantedprocessor or a non-implanted processor, such as a processor of aprogrammer or computer.

Referring now to FIGS. 3 through 6, subcutaneous cardiac sensing and/orstimulation devices and methods employing cardiac signal separation aredescribed in accordance with the present invention. The main principleof signal separation works on the premise that spatially distributedelectrodes collect components of a signal from a common origin (e.g.,the heart) with the result that these components will be stronglycorrelated to each other in time. In addition, these components willalso be weakly correlated to components of another origin (e.g., noise).The ITCS device may be implemented to separate these componentsaccording to their sources. To achieve this, the methods and algorithmsillustrated in FIGS. 3 through 6 may be implemented.

FIG. 3 illustrates a source separation system 125 in accordance with thepresent invention. A source separation process 414 is performed,providing a separated signal 419. The separated signal 419 is availablefor a variety of uses 420, such as, for example, arrhythmia detection,SVR (Supra-Ventricular Rhythm) confirmation, NSR (Normal Sinus Rhythm)confirmation, arrhythmia classification or other use.

FIG. 4 illustrates a signal source separation methodology 150 inaccordance with the present invention. After initiating 402 themethodology, a signal record process begins 404. During the signalrecord event 404, one or more electrode signals are recorded for laterprocessing, such as by signal source separation processing. Therecording may be continuous or performed for a given period of time. Atblock 406, a determination is made as to the presence or absence of anSVR using technology known in the art. If an SVR is detected, no otheraction is necessary, and recording and evaluation for SVR continues.

If SVR is absent, it is desirable to determine whether an adversecardiac condition exists, necessitating intervention, or whether thereis simply a spurious signal loss or other event not necessitatingintervention. A loss of SVR at decision 406 initiates a separationprocess 100, which will be described in greater detail below. After theseparation process 100 and any intervention steps deemed necessary arecompleted, a determination 408 is made as to whether other processing isnecessary. If no further processing is necessary, the recording process404 continues. If further processing is necessary, such additionalprocessing 410 is performed, along with any further action associatedwith processing 410, and then recording 404 continues.

FIG. 5 illustrates another embodiment of a signal source separationprocess 100 in accordance with the present invention. A set of compositesignals, including at least two and up to n signals, are selected forseparation, where n is an integer. Each electrode provides a compositesignal associated with an unknown number of sources. Pre-processingand/or pre-filtering 412 can be performed on each of the compositesignals. It may be advantageous to filter each composite signal usingthe same filtering function. Source separation 414 is performed,providing at least one separated signal. The separated signal can thenbe used 420 for some specified purpose, such as, for example, to confirma normal sinus rhythm, determine a cardiac condition, define a noisesignal, or other desired use.

If a treatment is desired, an appropriate treatment or therapy 418 isperformed. If continued source separation is desired, the processreturns to perform such source separation 414 and may iterativelyseparate 416 more signals until a desired signal is found, or allsignals are separated.

FIG. 6 illustrates further embodiments of a signal source separationprocess in greater detail, including some optional elements. Entry ofthe process at block 422 provides access to a pre-processing facility412, illustrated here as including a covariance matrix computation block424 and/or a pre-filtering block 426, such as, for example, a band-passfiltering block. The composite signals processed at pre-processing block412 are provided to a signal source separation block 415, which caninclude functionality of the source separation block 414 and iterativesource separation block 416 shown in FIG. 5.

The signal source separation block 415 includes a principal componentanalysis block 428, which produces an associated set of eigenvectors andeigenvalues using a covariance matrix or composite signals provided bypre-processing block 412. A determination 430 is made as to whether oneeigenvalue is significantly larger than any others in the set, makingthe dimension associated with this eigenvalue a likely candidate forassociation with the cardiac signal. If such a candidate is identifiedat block 430, the candidate signal may immediately be separated 431 anda determination 433 made to confirm whether the candidate signal is acardiac signal, before returning 444 to the master ITCS routine thatcalled the signal source separation process.

If there is no clear candidate eigenvalue, or if the largest valueeigenvalue did not provide a signal of interest, an iterative processmay be used to separate 432 and search 436 for the signal of interest(e.g., cardiac signal). This process 432, 436, 434 can be repeated untilsuch a signal is found, or no more signals are separable 434 asdetermined by exceeding a predefined number of iterations N_(max) orsome other termination criterion. An example of such a criterion is aneigenvalue considered at the current iteration being proportionatelysmaller than the largest eigenvalues by some predetermined amount.

If the iterations 434 are completed and a cardiac signal is not found at436, then an Independent Component Analysis 435 may be attempted tofurther process the signals in an attempt to find the cardiac signal. Ifa cardiac signal is still not found at decision 437, after exhaustingall possibilities, then a set of default settings 439 may be used, or anerror routine may be initiated.

With continued reference to FIGS. 3 through 6, one illustrative signalsource separation methodology according to the present invention isdescribed below. Such an approach is particularly well-suited for use inan ITCS system. It is to be understood that the example provided belowis provided for non-limiting, illustrative purposes only. Moreover, itis understood that signal source separation within the context of thepresent invention need not be implemented using the specific processesdescribed below, or each and every process described below.

A collected signal is preferably pre-filtered to suppress broadlyincoherent noise and to generally optimize the signal-to-noise ratio(SNR). Any noise suppression in this step has the additional benefit ofreducing the effective number of source signals that need to beseparated.

A Principal Component Analysis (PCA) is performed on the collectedand/or pre-filtered signal, producing a set of eigenvectors andassociated eigenvalues describing the optimal linear combination, in aleast-squares sense, of the recorded signals that makes the componentscoming from different sources orthogonal to one another. As anintermediate step to performing the PCA, an estimate of the spatialcovariance matrix may be computed and averaged over a relatively shorttime interval (on the order of 2–3 beats) to enhance those componentsthat are mutually correlated.

Each eigenvalue corresponds to the power of the signal projected alongthe direction of each associated eigenvector. The cardiac signalcomponent is typically identified by one of the largest eigenvalues.Occasionally, PCA does not achieve a substantially sufficient level ofsource independence. In such a case, an Independent Component Analysis(ICA) may be performed to determine the actual source direction, eitherupon the PCA-transformed signal, or directly upon the collected signal.The ICA consists of a unitary transformation based on higher-orderstatistical analysis. For example, separation of two mixed sources maybe achieved by rotating the complex variable formed from the signals onan angle that aligns their probability distributions with basis vectors.In another approach, an algorithm based on minimization of mutualinformation between components, as well as other approaches generallyknown in the field of ICA, may be used to achieve reconstructed sourceindependence.

FIG. 7 graphically depicts SNR improvement achievable by a signal sourceseparation methodology of the present invention. In this illustrativeexample, data was gathered under low-SNR conditions with electrocauterynoise using seven electrodes implanted in the thoracic region of a pig.The bottom subplot, identified as trace 452, represents the rawimplanted electrode signal. The next subplot, identified as trace 450,shows this signal after input filtering for optimal raw SNR using alinear-phase (4^(th)-order Bessel) band pass filter from 5 to 20 Hz. Thetop two subplots, identified as trace 448 and trace 446, illustrate theresulting separated components associated with the two largesteigenvalues. In this example, trace 446 is associated with theelectrocautery signal, having the largest eigenvalue. Trace 448 is theuncorrupted cardiac signal.

An ITCS device may, for example, employ a hierarchical decision-makingprocedure that initiates a blind source separation algorithm when noiseor arrhythmia is detected. By way of example, a local peak densityalgorithm or a curvature-based significant point methodology may be usedas a high-level detection routine.

The ITCS device may compute an estimate of the covariance matrix. It maybe sufficient to compute the covariance matrix for only a short time.Computation of the eigenvalues and eigenvectors required for the PCA mayalso be performed adaptively through an efficient updating algorithm.

The cardiac signal can be identified among the few (e.g., two or three)largest separated signals. One of several known algorithms may be used.For example, local peak density (LPD) or beat detection (BD) algorithmsmay be used. The LPD algorithm can be used to identify the cardiacsignal by finding a signal that has an acceptable physiologic range oflocal peak densities by comparing the LPD to a predetermined range ofpeak densities known to be acceptable. The BD algorithm will find asignal that has a physiologic range of beat rate. In the case where twosignals look similar, a morphology algorithm may be used for furtherdiscrimination. It may be beneficial to use the same algorithm atdifferent levels of hierarchy: 1) initiation of blind source separationalgorithm; 2) iterative identification of a cardiac signal.

Mathematical development of an exemplary blind source separationalgorithm in accordance with the present invention is provided asfollows. Assume there are m source signals s₁(t), . . . , s_(m)(t) thatare detected inside of the body, comprising a desired cardiac signal andsome other independent noise, which may, for example, includemyopotential noise, electrocautery response, etc. These signals arerecorded simultaneously from k sensing vectors derived from subcutaneoussensing electrodes, where k>m in a preferred approach. By definition,the signals are mixed together into the overall voltage gradient sensedacross the electrode array. In addition, there is usually an additivenoise attributable, for example, to environmental noise sources. Therelationship between the source signals s(t) and recorded signals x(t)is described below:

$\begin{matrix}{\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\vdots \\{x_{k}(t)}\end{pmatrix} = {\begin{pmatrix}{y_{1}(t)} \\{y_{2}(t)} \\\vdots \\{y_{k}(t)}\end{pmatrix} + \begin{pmatrix}{n_{1}(t)} \\{n_{2}(t)} \\\vdots \\{n_{k}(t)}\end{pmatrix}}} \\{= {{\begin{pmatrix}a_{11} & a_{12} & \ldots & a_{1m} \\a_{21} & a_{22} & \ldots & a_{2m} \\\vdots & \vdots & ⋰ & \vdots \\a_{k1} & a_{k2} & \ldots & a_{k\; m}\end{pmatrix}\begin{pmatrix}{s_{1}(t)} \\{s_{2}(t)} \\\vdots \\{s_{m}(t)}\end{pmatrix}} + \begin{pmatrix}{n_{1}(t)} \\{n_{2}(t)} \\\vdots \\{n_{k}(t)}\end{pmatrix}}} \\{= {x(t)}} \\{= {{y(t)} + {n(t)}}} \\{= \begin{matrix}{{{{As}(t)} + {n(t)}},} & \; & {m < k}\end{matrix}}\end{matrix}$

Here, x(t) is an instantaneous linear mixture of the source signals andadditive noise, y(t) is the same linear mixture without the additivenoise, n(t) is environmental noise modeled as Gaussian noise, A is anunknown mixing matrix, and s(t) are the unknown source signalsconsidered here to comprise the desired cardiac signal and otherbiological artifacts. There is no assumption made about the underlyingstructure of the mixing matrix and the source signals, except for theirspatial statistical independence. The objective is to reconstruct thesource signals s(t) from the recorded signals x(t).

Reconstruction of the source signals s(t) from the recorded signals x(t)preferably involves pre-filtering x(t) to optimize the SNR (i.e.,maximize the power of s(t) against that of n(t)). Here, a linear phasefilter can be used to minimize time-domain dispersion (tails andringing) and best preserve the underlying cardiac signal morphology. Itis noted that the notation x(t) is substituted for the pre-filteredversion of x(t).

An estimate of the spatial covariance matrix R is formed as shownimmediately below. This step serves to enhance the components of thesignal that are mutually correlated and downplays incoherent noise.

$\begin{matrix}{R = {\frac{1}{T_{({{\sim 1}\mspace{11mu}\sec})}}{\sum\limits_{{t = 1},T}{\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\ldots \\{x_{k}(t)}\end{pmatrix}*\begin{pmatrix}{x_{1}(t)} & {x_{2}(t)} & \ldots & {x_{k}(t)}\end{pmatrix}}}}} \\{= {\frac{1}{T_{({{\sim 1}\mspace{11mu}\sec})}}{\sum\limits_{{t = 1},T}\begin{bmatrix}{{x_{1}(t)}*{x_{1}(t)}} & {{x_{1}(t)}*{x_{2}(t)}} & \ldots & {{x_{1}(t)}*{x_{k}(t)}} \\{{x_{2}(t)}*{x_{1}(t)}} & {{x_{2}(t)}*{x_{2}(t)}} & \ldots & {{x_{2}(t)}*{x_{k}(t)}} \\\ldots & \ldots & ⋰ & \ldots \\{{x_{k}(t)}*{x_{1}(t)}} & {{x_{k}(t)}*{x_{2}(t)}} & \ldots & {{x_{k}(t)}*{x_{k}(t)}}\end{bmatrix}}}}\end{matrix}$

Eigenvalues and eigenvectors of the covariance matrix R may bedetermined using singular value decomposition (SVD). By definition, theSVD factors R as a product of three matrices R=USV^(T), where U and Vare orthogonal matrices describing amplitude preserving rotations, and Sis a diagonal matrix that has the squared eigenvalues σ₁ . . . σ_(k) onthe diagonal in monotonically decreasing order. Expanded into elements,this SVD may be expressed as follows.

$R = {\begin{pmatrix}u_{11} & u_{12} & \ldots & u_{1k} \\u_{21} & u_{22} & \ldots & u_{2k} \\\vdots & \vdots & ⋰ & \vdots \\u_{k1} & u_{k2} & \ldots & u_{kk}\end{pmatrix}\begin{pmatrix}\sigma_{1} & 0 & 0 & 0 \\0 & \sigma_{2} & 0 & 0 \\\vdots & \vdots & ⋰ & \vdots \\0 & 0 & \ldots & \sigma_{k}\end{pmatrix}\begin{pmatrix}v_{11} & v_{12} & \ldots & v_{1k} \\v_{21} & v_{22} & \ldots & v_{2k} \\\vdots & \vdots & ⋰ & \vdots \\v_{k1} & v_{k2} & \ldots & v_{kk}\end{pmatrix}}$

The columns of matrix V consist of eigenvectors that span a newcoordinate system wherein the components coming from different sourcesare orthogonal to one another. Eigenvalues σ₁ . . . σ_(k) correspondrespectively to columns 1 . . . k of V. Each eigenvalue defines thesignal “power” along the direction of its corresponding eigenvector. Thematrix Vthus provides a rotational transformation of x(t) into a spacewhere each separate component of x is optimally aligned, in aleast-squares sense, with a basis vector of that space.

The largest eigenvalues correspond to the highest power components,which typically represent the mixed source signals y₁(t), . . .,y_(m)(t). The lower eigenvalues typically are associated with additivenoise n₁(t), . . . ,n_(k-m)(t). Each eigenvector may then be viewed asan optimal linear operator on x that maximizes the power of thecorresponding independent signal component. As a result, the transformedsignal is found as:

${\hat{y}(t)} = {\begin{pmatrix}{{\hat{y}}_{1}(t)} \\\vdots \\{{\hat{y}}_{m}(t)}\end{pmatrix} = {\begin{pmatrix}v_{11} & v_{21} & \ldots & v_{k1} \\\vdots & \vdots & ⋰ & \vdots \\v_{1m} & v_{2m} & \ldots & v_{k\; m}\end{pmatrix}*\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\vdots \\{x_{k}(t)}\end{pmatrix}}}$

The component estimates ŷ₁(t), . . . , ŷ_(m)(t) of y₁(t), . . . ,y_(m)(t) are aligned with the new orthogonal system of coordinatesdefined by eigenvectors. As a result, they should be orthogonal to eachother and thus independent.

In an alternative implementation, eigenvalues and eigenvectors of thecovariance matrix R may be determined using eigenvalue decomposition(ED). By definition, the ED solves the matrix equation RV=SV so that Sis a diagonal matrix having the eigenvalues σ₁ . . . σ_(k) on thediagonal, preferably in monotonically decreasing order, and so thatmatrix V contains the corresponding eigenvectors along its columns. Theresulting eigenvalues and associated eigenvectors may be applied insimilar manner to those resulting from the SVD of covariance matrix R.

In an alternative implementation, eigenvalues and eigenvectors arecomputed directly from x(t) by forming a rectangular matrix X of ksensor signals collected during a time segment of interest, andperforming an SVD directly upon X. The matrix X and its decompositionmay be expressed as follows.

$X = {\begin{pmatrix}{x_{1}(t)} \\{x_{2}(t)} \\\vdots \\{x_{k}(t)}\end{pmatrix} = {\begin{pmatrix}{x_{1}\left( t_{1} \right)} & {x_{1}\left( t_{2} \right)} & \ldots & {x_{1}\left( t_{T} \right)} \\{x_{2}\left( t_{1} \right)} & {x_{2}\left( t_{2} \right)} & \cdots & {x_{2}\left( t_{T} \right)} \\\vdots & \vdots & ⋰ & \vdots \\{x_{k}\left( t_{1} \right)} & {x_{k}\left( t_{2} \right)} & \cdots & {x_{k}\left( t_{T} \right)}\end{pmatrix} = {USV}^{T}}}$

Note that in cases where T>k, a so-called “economy-size” SVD may be usedto find the eigenvalues and eigenvectors efficiently. Such an SVD may beexpressed as follows, expanded into elements.

$\begin{matrix}{X = {USV}^{T}} \\{= {\begin{pmatrix}u_{11} & u_{12} & \ldots & u_{1T} \\u_{21} & u_{22} & \ldots & u_{2T} \\\vdots & \vdots & ⋰ & \vdots \\u_{k1} & u_{k2} & \ldots & u_{kT}\end{pmatrix}\begin{pmatrix}\sigma_{1} & 0 & \ldots & 0 \\0 & \sigma_{2} & \ldots & 0 \\\vdots & \vdots & ⋰ & \vdots \\0 & 0 & \ldots & \sigma_{k}\end{pmatrix}\begin{pmatrix}v_{11} & v_{12} & \ldots & v_{1k} \\v_{21} & v_{22} & \ldots & v_{2k} \\\vdots & \vdots & ⋰ & \vdots \\v_{k1} & v_{k2} & \ldots & v_{kk}\end{pmatrix}}}\end{matrix}$

A similar economy-sized SVD may also be used for the less typical casewhere k>T. The matrices S and V resulting from performing the SVD ofdata matrix X may be applied in the context of this present inventionidentically as the matrices S and V resulting from performing the SVD onthe covariance matrix R.

At this point, the mutual separation of ŷ₁(t), . . . , ŷ_(m)(t) would becompleted, based on the covariance statistics. Occasionally, informationfrom covariance is not sufficient to achieve source independence. Thishappens, for example, when the cardiac signal is corrupted withelectrocautery, which may cause perturbations from the linearly additivenoise model. In such a case, Independent Component Analysis (ICA) can beused to further separate the signals.

The ICA seeks to find a linear transformation matrix W that inverts themixing matrix A in such manner as to recover an estimate of the sourcesignals. The operation may be described as follows.

${s(t)} = {\begin{pmatrix}{s_{1}(t)} \\{s_{2}(t)} \\\vdots \\{s_{m}(t)}\end{pmatrix} = {{W\mspace{11mu}{y(t)}} \approx {A^{- 1}{y(t)}}}}$

Here we substitute s(t) for the recovered estimate of the sourcesignals. The signal vector y(t) corresponds to either the collectedsensor signal vector x(t) or to the signal ŷ(t) separated with PCA. Thematrix W is the solution of an optimization problem that maximizes theindependence between the components s₁(t), . . . , s_(m)(t) ofs(t)=Wy(t). We treat the components of s(t) as a vector of randomvariables embodied in the vector notation s, so that the desiredtransformation would optimize some cost function C(s)=C([s₁(t), . . . ,s_(m)(t)]) that measures the mutual independence of these components.Given the joint probability density function (pdf) f (s) and thefactorized pdf f(S)=f₁(s₁) f₂(s₂) . . . f_(m)(s_(m)), or given estimatesof these pdf's, we may solve the following.

${\begin{matrix}\min \\W\end{matrix}{C(s)}} = {\begin{matrix}\min \\W\end{matrix}{\int{{D\left( {{f(s)},{\overset{\_}{f}(s)}} \right)}{\mathbb{d}s}}}}$

The function D(f (s), f(s)) may be understood as a standard distancemeasure generally known in the art, such as for example an absolutevalue difference |f(s)− f(s)|, Euclidean distance (f(s)− f(s))², orp-norm (f(s)− f(s))^(p). The distance measure approaches zero as f(s)approaches f(s), which by the definition of statistical independence,occurs as the components of s approach mutual statistical independence.

In an alternative implementation, the distance measure may take the formof a Kullback-Liebler divergence (KLD) between f(s) and f(s), yieldingcost function optimizations in either of the following forms.

$\begin{matrix}{{\begin{matrix}\min \\W\end{matrix}{C(s)}} = {\begin{matrix}\min \\W\end{matrix}{\int{{f(s)}\mspace{11mu}\log\;\frac{f(s)}{\overset{\_}{f}(s)}{\mathbb{d}s}}}}} \\{or} \\{\mspace{101mu}{= {\begin{matrix}\min \\W\end{matrix}{\int{{\overset{\_}{f}(s)}\mspace{11mu}\log\;\frac{\overset{\_}{f}(s)}{f(s)}{\mathbb{d}s}}}}}}\end{matrix}$

Since the KLD is not symmetric, the two alternative measures are relatedbut not precisely equal. One measure could be chosen, for example, if aparticular underlying data distribution favors convergence with thatmeasure.

Several alternative approaches may be used to measure the mutualindependence of the components of s. These may include the maximumlikelihood method, maximization of negentropy or its approximation, andminimization of mutual information.

In the maximum likelihood method, the desired matrix W is found as asolution of the following optimization problem,

$\begin{matrix}{{{\max\limits_{W}{\sum\limits_{j = 1}^{T}{\sum\limits_{i = 1}^{m}{\log\mspace{11mu}{f_{i}\left( {s_{i}\left( t_{j} \right)} \right)}}}}} + {T\mspace{11mu}\log\;{{\det\; W}}}} = {{\max\limits_{W}{\sum\limits_{j = 1}^{T}{\sum\limits_{i = 1}^{m}{\log\mspace{11mu} f_{i}\left( {w_{i}^{T}{y\left( t_{j} \right)}} \right)}}}} +}} \\{T\mspace{11mu}\log\;{{\det\; W}}}\end{matrix}$

where w_(i) are columns of the matrix W. In the negentropy method, thecost function is defined in terms of differences in entropy between sand a corresponding Gaussian random variable, resulting in the followingoptimization problem,

${\max\limits_{W}\left\{ {{H\left( s_{gauss} \right)} - {H(s)}} \right\}} = {\max\limits_{W}\left\{ {{- {\int{{f\left( s_{gauss} \right)}\log\;{f\left( s_{gauss} \right)}{\mathbb{d}s_{gauss}}}}} + {\int{{f(s)}{\log(s)}{\mathbb{d}s}}}} \right\}}$where H(s) is the entropy of random vector s, and s_(gauss) is aGaussian random vector chosen to have a covariance matrix substantiallythe same as that of s.

In the minimization of mutual information method, the cost function isdefined in terms of the difference between the entropy of s and the sumof the individual entropies of the components of s, resulting in thefollowing optimization problem.

$\min\limits_{W}\left\{ {{- \;{\sum\limits_{i = 1}^{m}{\int{{f\left( s_{i} \right)}\;\log\;{f\left( s_{i} \right)}{\mathbb{d}s_{i}}}}}} + {\int{{f(s)}\;\log\;{f(s)}{\mathbb{d}s}}}} \right\}$

All preceding cost function optimizations having an integral form may beimplemented using summations by approximating the underlying pdf s withdiscrete pdf's, for example as the result of estimating the pdf usingwell-known histogram methods. We note that knowledge of the pdf, or evenan estimate of the pdf, can be difficult to implement in practice dueeither to computational complexity, sparseness of available data, orboth. These difficulties may be addressed using cost functionoptimization methods based upon kurtosis, a statistical parameter thatdoes not require a pdf.

In an alternative method, a measure of independence could be expressedvia kurtosis, equivalent to the fourth-order statistic defined as thefollowing for the i^(th) component of s.kurt(s _(i))=E{s _(i) ⁴}−3(E{s _(i) ²})²

In this case W is found as a matrix that maximizes kurtosis of s=Wy overall the components of s (understanding y to be a vector of randomvariables corresponding to the components of y(t)). In all the previousexamples of ICA optimization the solution W could be found via numericalmethods such as steepest descent, Newton iteration, etc., well known andestablished in the art. These methods could prove numerically intensiveto implement in practice, particularly if many estimates of statisticsin s must be computed for every iteration in W.

Computational complexity can be addressed by several means. To begin,the ICA could be performed on the PCA-separated signal ŷ(t) with thedimensionality reduced to only the first few (or in the simplest case,two) principal components. For situations where two principal componentsare not sufficient to separate the sources, the ICA could still beperformed pairwise on two components at a time, substituting componentpairs at each iteration of W (or group of iterations of W).

In one example, a simplified two-dimensional ICA may be performed on thePCA separated signals. In this case, a unitary transformation could befound as a Givens rotation matrix with rotation angle θ,

${W(\theta)} = \begin{pmatrix}{\cos\;\theta} & {\sin\;\theta} \\{{- \sin}\;\theta} & {\cos\;\theta}\end{pmatrix}$where s(t)=W(θ)y(t). Here W(θ) maximizes the probability distribution ofeach component along the basis vectors, such that the following issatisfied.

$\theta = {\arg\;{\max\limits_{\theta}{\sum\limits_{t = 1}^{T}\;{\log\;{f\left( {s(t)} \middle| \theta \right)}}}}}$

This optimal rotation angle may be found by representing vectors y(t)and s(t)ξ=e ^(i4θ) E(ρ⁴ e ^(i4φ′))=e ^(i4θ) E[(s ₁ +is ₂)⁴ ]=e ^(i4θ)(κ₄₀^(s)+κ₀₄ ^(s))as complex variables in the polar coordinate form y=y₁+iy₂=ρe^(iφ),s=s₁+is₂=ρe^(iφ′) and finding the relationships between their phaseangles φ, φ′:φ=φ′+θ, where θ is the rotation that relates the vectors.Then, the angle θ may be found from the fourth order-statistic of acomplex variable ξ, where κ^(s) is kurtosis of the signal s(t).

By definition, source kurtosis is unknown, but may be found based on thefact that the amplitude of the source signal and mixed signals are thesame.

As a result, 4θ={circumflex over (ξ)}sign({circumflex over (γ)})with γ=E[ρ ⁴]−8=κ₄₀ ^(s)+κ₀₄ ^(s) and ρ² =s ₁ ² +s ₂ ² =y ₁ ² +y ₂ ²

In summary, the rotation angle can be estimated as:

$\theta = {\frac{1}{4}\mspace{14mu}{angle}\mspace{11mu}\left( {\hat{\xi}\;{sign}\;\left( \hat{\gamma} \right)} \right)\mspace{20mu}{where}}$${\hat{\xi} = {{\frac{1}{T}{\sum\limits_{{t = 1},T}{\rho_{t}^{4}{\mathbb{e}}^{{\mathbb{i}}\; 4\;{\varphi{(t)}}}}}} = {\frac{1}{T}{\sum\limits_{{t = 1},T}\left( {{y_{1}(t)} + {i\;{y_{2}(t)}}} \right)^{4}}}}},{\hat{\gamma} = {{{\frac{1}{T}{\sum\limits_{{t = 1},T}\rho_{t}^{4}}} - 8} = {{\frac{1}{T}{\sum\limits_{{t = 1},T}\left( {{y_{1}^{2}(t)} + {i\;{y_{2}^{2}(t)}}} \right)^{4}}} - 8}}}$

After the pre-processing step, the cardiac signal is normally the firstor second most powerful signal. In addition, there is usually inpractice only one source signal that is temporally white. In this case,rotation of the two-dimensional vector y=y₁+iy₂=ρe^(iφ) is all that isrequired. In the event that more than two signals need to be separated,the Independent Component Analysis process may be repeated in pair-wisefashion over the m(m−1)/2 signal pairs until convergence is reached,usually taking about (1+√{square root over (m)})iterations.

An ITCS device that implements the above-described processes mayrobustly separate the cardiac signal from a low SNR signal recorded fromthe implantable device. Such an ITCS device robustly separates cardiacsignals from noise to allow for improved sensing of cardiac rhythms andarrhythmias.

The system operates by finding a combination of the spatially collectedlow SNR signals that makes cardiac signal and noise orthogonal to eachother (independent). This combination achieves relatively cleanextraction of the cardiac signal even from negative SNR conditions.

An ITCS device may operate in a batch mode or adaptively, allowing foron-line or off-line implementation. To save power, the system mayinclude the option for a hierarchical decision-making routine that usesalgorithms known in the art for identifying presence of arrhythmias ornoise in the collected signal and turning on the cardiac signalextraction routine.

Various modifications and additions can be made to the preferredembodiments discussed hereinabove without departing from the scope ofthe present invention. Accordingly, the scope of the present inventionshould not be limited by the particular embodiments described above, butshould be defined only by the claims set forth below and equivalentsthereof.

1. A signal separation method, comprising: detecting a plurality ofcomposite signals at a plurality of subcutaneous non-intrathoraciclocations, the plurality of composite signals associated with aplurality of sources; separating a signal from the plurality ofcomposite signals using blind source separation; and identifying theseparated signal as a cardiac signal.
 2. The method of claim 1, furthercomprising iteratively separating signals from the plurality ofcomposite signals until the cardiac signal is identified.
 3. The methodof claim 1, wherein the plurality of composite signals comprises thecardiac signal and at least one non-cardiac signal.
 4. The method ofclaim 1, wherein the blind source separation comprises a principalcomponent analysis.
 5. The method of claim 4, wherein the principalcomponent analysis includes a singular value decomposition.
 6. Themethod of claim 4, wherein the principal component analysis includes aneigenvalue decomposition.
 7. The method of claim 1, wherein the blindsource separation comprises an independent component analysis.
 8. Themethod of claim 1, wherein the blind source separation comprises aprincipal component analysis and an independent component analysis. 9.The method of claim 1, further comprising filtering each of theplurality of composite signals before separating the signal.
 10. Themethod of claim 1, further comprising band-pass filtering each of theplurality of composite signals.
 11. The method of claim 1, furthercomprising determining a cardiac condition using the cardiac signal. 12.The method of claim 1, further comprising detecting a cardiac conditionusing the separated signal, wherein detecting the cardiac conditioncomprises performing a rate based analysis of the cardiac signal. 13.The method of claim 1, further comprising detecting a cardiac conditionusing the separated signal, wherein detecting the cardiac conditioncomprises performing a morphology based analysis of the cardiac signal.14. The method of claim 1, further comprising detecting a cardiaccondition using the separated signal, wherein detecting the cardiaccondition comprises performing a pattern and rate based analysis of thecardiac signal.
 15. The method of claim 1, further comprising detectinga cardiac condition using the cardiac signal and implantably treatingthe cardiac condition.
 16. The method of claim 15, wherein implantablytreating the cardiac condition comprises delivering a cardiacstimulation therapy.
 17. The method of claim 15, wherein implantablytreating the cardiac condition comprises delivering a cardiacstimulation therapy using an implanted subcutaneous non-intrathoracicelectrode.
 18. The method of claim 15, wherein detecting the pluralityof composite signals at the plurality of subcutaneous locationscomprises using a subcutaneous non-intrathoracic electrode array andwherein implantably treating the cardiac condition comprises using theelectrode array to provide a cardiac stimulation therapy.
 19. The methodof claim 1, further comprising: forming a composite signal matrix fromthe plurality of composite signals; and performing a principal componentanalysis on the composite signal matrix, thereby producing a set ofeigenvalues and associated eigenvectors.
 20. The method of claim 19,wherein an eigenvector of the associated eigenvectors that is associatedwith a largest magnitude eigenvalue of the set of eigenvalues is used toseparate the signal from the plurality of composite signals.
 21. Themethod of claim 20, wherein the signal is separated from the pluralityof composite signals by multiplying the composite signal matrix by theeigenvector.
 22. The method of claim 20, wherein the signal is separatediteratively from the plurality of composite signals using an eigenvectorassociated with a next-largest magnitude eigenvalue for each iteration,until the cardiac signal is identified.
 23. The method of claim 22,wherein the cardiac signal is identified using a local peak density ofthe separated signal, wherein the local peak density is within apredetermined range.
 24. The method of claim 22, wherein the cardiacsignal is identified using beat detection on the separated signal,wherein a beat rate is within a predetermined range.
 25. The method ofclaim 22, wherein the cardiac signal is identified using a local rate ofoccurrence of significant points in the separated signal, wherein thelocal rate of occurrence is within a predetermined range.
 26. The methodof claim 22, wherein the cardiac signal is identified using a morphologyof the separated signal, wherein the morphology satisfies aphysiological characteristic.
 27. The method of claim 19, furthercomprising forming an intermediate signal matrix by multiplying thecomposite signal matrix by a matrix composed of the eigenvectorscorresponding to at least the two largest eigenvalues, and finding aunitary matrix corresponding to a rotational transformation of theintermediate signal matrix that increases the independence of theintermediate signals.
 28. The method of claim 27, further comprisingforming an independent signal matrix by multiplying the intermediatesignal matrix by the unitary matrix, wherein the independent signalmatrix comprises a set of independent signal vectors.
 29. The method ofclaim 28, wherein a signal vector from the set of independent signalvectors is iteratively examined until a cardiac signal is identified.30. The method of claim 29, wherein the cardiac signal is identifiedusing a local peak density of the examined signal, wherein the localpeak density is within a predetermined range.
 31. The method of claim29, wherein the cardiac signal is identified using beat detection on theexamined signal, wherein a beat rate is within a predetermined range.32. The method of claim 29, wherein the cardiac signal is identifiedusing a local rate of occurrence of significant points in the examinedsignal, wherein the local rate of occurrence is within a predeterminedrange.
 33. The method of claim 29, wherein the cardiac signal isidentified using a morphology of the examined signal, wherein themorphology satisfies a physiological characteristic.
 34. The method ofclaim 1, further comprising forming an estimate of a spatial covariancematrix for a composite signal matrix formed from the plurality ofcomposite signals.
 35. The method of claim 34, further comprisingperforming a principal component analysis on the estimate of the spatialcovariance matrix, producing a set of eigenvalues and associatedeigenvectors.
 36. The method of claim 35, wherein an eigenvector of theassociated eigenvectors that is associated with a largest magnitudeeigenvalue of the set of eigenvalues is used to separate the signal fromthe plurality of composite signals.
 37. The method of claim 36, whereinthe signal is separated from the plurality of composite signals bymultiplying the composite signal matrix by the eigenvector.
 38. Themethod of claim 36, wherein the signal is separated iteratively from theplurality of composite signals using an eigenvector associated with anext-largest magnitude eigenvalue for each iteration, until the cardiacsignal is identified.
 39. The method of claim 38, wherein the cardiacsignal is identified using a local peak density of the separated signal,wherein the local peak density is within a predetermined range.
 40. Themethod of claim 38, wherein the cardiac signal is identified using beatdetection on the separated signal, wherein a beat rate is within apredetermined range.
 41. The method of claim 38, wherein the cardiacsignal is identified using a local rate of occurrence of significantpoints in the separated signal, wherein the local rate of occurrence iswithin a predetermined range.
 42. The method of claim 38, wherein thecardiac signal is identified using a morphology of the separated signal,wherein the morphology satisfies a physiological characteristic.
 43. Themethod of claim 35, further comprising forming an intermediate signalmatrix by multiplying the composite signal matrix by a matrix composedof the eigenvectors corresponding to at least the two largesteigenvalues, and finding a unitary matrix corresponding to a rotationaltransformation of the intermediate signal matrix that increases theindependence of the intermediate signals.
 44. The method of claim 43,further comprising forming an independent signal matrix by multiplyingthe intermediate signal matrix by the unitary matrix, wherein theindependent signal matrix comprises a set of independent signal vectors.45. The method of claim 44, wherein a signal vector from the set ofindependent signal vectors is iteratively examined until a cardiacsignal is identified.
 46. The method of claim 45, wherein the cardiacsignal is identified using a local peak density of the examined signal,wherein the local peak density is within a predetermined range.
 47. Themethod of claim 45, wherein the cardiac signal is identified using beatdetection on the examined signal, wherein a beat rate is within apredetermined range.
 48. An implantable cardiac device, comprising: aplurality of electrodes configured for subcutaneous non-intrathoracicsensing; and a signal processor coupled to the plurality of electrodes,the signal processor configured to receive a composite signal associatedwith a plurality of sources sensed by at least two of the electrodes,and to extract a cardiac signal from the plurality of composite signalsusing blind source separation.
 49. The device of claim 48, furthercomprising at least one lead coupled to the plurality of subcutaneousnon-intrathoracic electrodes.
 50. The device of claim 48, furthercomprising a plurality of leads coupled to the plurality of subcutaneousnon-intrathoracic electrodes.
 51. The device of claim 48, furthercomprising a plurality of leads, wherein at least one of the pluralityof leads is coupled to an array of electrodes.
 52. The device of claim48, wherein the signal processor further comprises an adaptive filter,the adaptive filter altering its filtering characteristics based on alevel of ambient noise.
 53. The device of claim 52, wherein the level ofambient noise is determined using the independent component analysis.54. The device of claim 48, wherein the blind source separation includesa principal component analysis that produces a set of eigenvalues andassociated eigenvectors, and an eigenvector with a largest magnitudeeigenvalue is used to extract the cardiac signal from the plurality ofcomposite signals.
 55. The device of claim 54, wherein a signal isseparated iteratively from the plurality of composite signals using anext-largest magnitude eigenvalue for each iteration, until the cardiacsignal is extracted from the plurality of composite signals.
 56. Animplantable cardiac device, comprising: means for subcutaneouslydetecting a plurality of composite signals produced by a plurality ofsources; means for separating a signal from the plurality of compositesignals “using blind source separation”;and means for identifying theseparated signal as a cardiac signal.
 57. The device of claim 56,wherein the separating means performs a principal component analysis onthe plurality of composite signals.
 58. The device of claim 56, whereinthe separating means produces a set of eigenvalues and associatedeigenvectors, and an eigenvector with a largest magnitude eigenvalue isused for separating the signal from the plurality of composite signals.59. The device of claim 58, wherein the separating means iterativelyseparates the signal from the plurality of composite signals using anext-largest magnitude eigenvalue for each iteration, until the cardiacsignal is separated from the plurality of composite signals.
 60. Thedevice of claim 56, further comprising means for detecting a cardiaccondition using the cardiac signal.
 61. The device of claim 60, furthercomprising means for treating the cardiac condition.